Groupwise Geometric and Photometric Direct Image Registration

Image registration consists in estimating geometric and photometric transformations that align two images as best as possible. The direct approach consists in minimizing the discrepancy in the intensity or color of the pixels. The inverse compositional algorithm has been recently proposed by Baker e...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence Jg. 30; H. 12; S. 2098 - 2108
1. Verfasser: Bartoli, A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Los Alamitos, CA IEEE 01.12.2008
IEEE Computer Society
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Schlagworte:
Algorithm design and analysis
Algorithms
and thresholding
Applied sciences
Artificial Intelligence
Cameras
color
Computational efficiency
Computational modeling
Computer Science
Computer science; control theory; systems
Computer vision
Computer Vision and Pattern Recognition
Convergence
Deformable models
Estimating
Exact sciences and technology
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image registration
Intensity
Inverse
Pattern Recognition, Automated - methods
Pattern recognition. Digital image processing. Computational geometry
Photometry
Pixels
Reproducibility of Results
Robot vision systems
Sensitivity and Specificity
Solid modeling
Studies
Subtraction Technique
Transformations
Computer vision
color
photometry
Intensity
and thresholding
Geometric transformation
Image registration
Image processing
photometric transformation
Lighting
Updating
geometric warp
inverse composition
Pattern analysis
Artificial intelligence
Photometry
ISSN:0162-8828, 1939-3539
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Image registration consists in estimating geometric and photometric transformations that align two images as best as possible. The direct approach consists in minimizing the discrepancy in the intensity or color of the pixels. The inverse compositional algorithm has been recently proposed by Baker et al. for the direct estimation of groupwise geometric transformations. It is efficient in that it performs several computationally expensive calculations at a pre-computation phase. Photometric transformations act on the value of the pixels. They account for effects such as lighting change. Jointly estimating geometric and photometric transformations is thus important for many tasks such as image mosaicing. We propose an algorithm to jointly estimate groupwise geometric and photometric transformations while preserving the efficient pre-computation based design of the original inverse compositional algorithm. It is called the dual inverse compositional algorithm. It uses different approximations than the simultaneous inverse compositional algorithm and handles groupwise geometric and global photometric transformations. Its name stems from the fact that it uses an inverse compositional update rule for both the geometric and the photometric transformations. We demonstrate the proposed algorithm and compare it to previous ones on simulated and real data. This shows clear improvements in computational efficiency and in terms of convergence.
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ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2008.22